Identifying and Mitigating Algorithmic Bias in Student Emotional Analysis

Author:

Ashwin T. S.ORCID,Biswas GautamORCID

Publisher

Springer Nature Switzerland

Reference21 articles.

1. Anderson, H., Boodhwani, A., Baker, R.S.: Assessing the fairness of graduation predictions. In: Proceedings of the 12th International Conference on Educational Data Mining, pp. 488–491 (2019)

2. Ashwin, T., Guddeti, R.M.R.: Affective database for e-learning and classroom environments using Indian students’ faces, hand gestures and body postures. Futur. Gener. Comput. Syst. 108, 334–348 (2020)

3. Baker, R.S., Hawn, A.: Algorithmic bias in education. Int. J. Artif. Intell. Educ. 1–41 (2021)

4. Biswas, G., Segedy, J.R., Bunchongchit, K.: From design to implementation to practice a learning by teaching system: betty’s brain. Int. J. Artif. Intell. Educ. 26, 350–364 (2016)

5. Christie, S.T., Jarratt, D.C., Olson, L.A., Taijala, T.T.: Machine-learned school dropout early warning at scale. In: International Educational Data Mining Society (2019)

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